A Method to Study the Correlation Between Local Collagen Structure and Mechanical Properties of Atherosclerotic Plaque Fibrous Tissue

Hanneke Crielaard*, Su Guvenir Torun, Tamar B. Wissing, Pablo de Miguel Muñoz, Gert Jan Kremers, Frank J.H. Gijsen, Kim Van Der Heiden, Ali C. Akyildiz

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

The rupture of atherosclerotic plaques in coronary and carotid arteries is the primary cause of fatal cardiovascular events. However, the rupture mechanics of the heterogeneous, highly collagenous plaque tissue, and how this is related to the tissue's fibrous structure, are not known yet. Existing pipelines to study plaque mechanics are limited to obtaining only gross mechanical characteristics of the plaque tissue, based on the assumption of structural homogeneity of the tissue. However, fibrous plaque tissue is structurally heterogeneous, arguably mainly due to local variation in the collagen fiber architecture. The mechano-imaging pipeline described here has been developed to study the heterogeneous structural and mechanical plaque properties. In this pipeline, the tissue's local collagen architecture is characterized using multiphoton microscopy (MPM) with second-harmonic generation (SHG), and the tissue's failure behavior is characterized under uniaxial tensile testing conditions using digital image correlation (DIC) analysis. This experimental pipeline enables correlation of the local predominant angle and dispersion of collagen fiber orientation, the rupture behavior, and the strain fingerprints of the fibrous plaque tissue. The obtained knowledge is key to better understand, predict, and prevent atherosclerotic plaque rupture events.

Original languageEnglish
Article numbere64334
JournalJournal of Visualized Experiments
Volume2022
Issue number189
DOIs
Publication statusPublished - 11 Nov 2022

Bibliographical note

Funding Information:
This work was funded by an NWO-Vidi grant (18360).

Publisher Copyright:
© 2022 JoVE Creative Commons Attribution-NonCommercial-NoDerivs 3.0 Unported License.

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